Banking crises and financial instability: Empirical and historical lessons

The paper examines the importance of financial instability for the development of four Norwegian banking crises. The crises are the Post First World War Crisis during the early 1920s, the mid 1920s Monetary Crisis, the Great Depression in the 1930s, and the Scandinavian Banking Crisis of 1987–1993. The paper first offers a description of the financial instability hypothesis applied by Minsky and Kindleberger, and in a recent dynamic financial crisis model. Financial instability is defined as a lack of financial markets and institutions that provide capital and liquidity at a sustainable level under stress. Financial instability basically evolves during times of overheating, overspending and extended credit granting. This is most common during significant booms. The process has devastating effects after markets have turned into a state of negative development.The paper tests the validity of the financial instability hypothesis using a quantitative structural time series model. It reveals upheaval of 10 financial and macroeconomic indicators prior to all the four crises, resulting in a state of economic overheating and asset bubble creation. This is basically explained by huge growth in debts. The overheating caused the following banking crises. Finally, the paper discusses the four crises qualitatively. Again, the conclusion is that a significant increase in money supply and debt caused overheating, asset bubbles, and thereafter, financial and banking crises, which in turn spread to other markets and industries and caused huge slumps in the real economy.

THE INTER-TIER SPREAD OF HOUSING BUBBLES: ARE LUXURY MARKETS TO BLAME?

Understanding the spread of asset bubbles is pivotal to the effectiveness of risk management. This study thus estimates housing bubbles and investigates how and to what extent price bubbles spread between the tiers of luxury and mass housing in Hong Kong. The results show that price bubbles spread between housing tiers, the spreading of bubbles is not uni-directional from luxury to mass tiers, and more than 60% of bubbles come from inter-tier spreading. Moreover, bubble shocks from the luxury tier have stronger spreading influences on the movements of bubbles in the mass housing tier than the other way around during the period before the end of the global financial crisis (GFC), whereas the opposite is true for the period after GFC. The findings are important for policy makers attempting to tackle soaring housing bubbles, financial institutions seeking to managing lending risk, and housing investors wanting to time the submarkets.

Can You Hear the Shape of a Market? Geometric Arbitrage and Spectral Theory

Utilizing gauge symmetries, the Geometric Arbitrage Theory reformulates any asset model, allowing for arbitrage by means of a stochastic principal fibre bundle with a connection whose curvature measures the “instantaneous arbitrage capability”. The cash flow bundle is the associated vector bundle. The zero eigenspace of its connection Laplacian parameterizes all risk-neutral measures equivalent to the statistical one. A market satisfies the No-Free-Lunch-with-Vanishing-Risk (NFLVR) condition if and only if 0 is in the discrete spectrum of the Laplacian. The Jarrow–Protter–Shimbo theory of asset bubbles and their classification and decomposition extend to markets not satisfying the NFLVR. Euler’s characteristic of the asset nominal space and non-vanishing of the homology group of the cash flow bundle are both topological obstructions to NFLVR.

Asset bubbles in explaining top income shares

This paper considers the role of asset price bubbles (crashes) as an important determinant in seeking a further explanation for top income shares. The asset price bubbles caused at least in part by monetary policies, along with other determinants such as top tax rates and innovativeness are the important drivers to explain the surge in top income shares. The empirical results show that correlation between asset bubbles and top inequality is positive and significant. The regression coefficient of stock and housing market bubbles have a positive effect on top income shares, while the stock and housing market crashes fail to reduce the surge in top income shares. In sum, as the asset markets grow, the share of income going to those at the very top increases and the accumulation of income accelerates if the duration of bubbles expands. Concentration of income at the very top is much more important when capital gains are counted as income.

Financial Contagion: A Tale of Three Bubbles

The primary purpose of the study is to identify and measure the properties of asset bubbles, volatility clustering, and financial contagion during three recent financial market anomalies that originated in the U.S. and Chinese markets. In particular, we focus on the 2000 DotCom Bubble, the 2008 Housing Crisis, and the 2015 Chinese Bubble. We employ three main empirical methods; the LPPL model to identify asset bubbles, the DCC-GARCH model to measure volatility clustering, and the Diebold-Yilmaz volatility spillover index to measure the level of financial contagion. We provide robust evidence that during the DotCom bubble there was very limited spillover between the S&P 500, the Shanghai, and the Shenzhen Composite Indexes. However, there was significantly more spillover effects in the two more recent crises, i.e., the Housing crisis and the 2015 Chinese Bubble. Together, these results highlight the fact that as financial markets have become more globalized, there are greater levels of volatility transmission and correspondingly fewer potential benefits from international diversification.

Schumpeter’s creative destruction and the credit crunch of 2007–2008: an Islamic banking perspective

Purpose This paper aims to compare products traded in secular and Islamic banking environments prior to the credit crunch of 2007–2008; to locate the comparison in a Schumpeterian model of creative destruction of dynamic innovation in the capital markets; and to evaluate the implications for diversity of investor product choice. Design/methodology/approach Financial products are critiqued using qualitative criteria, including underestimation of risk implicit in mortgage-backed securities and securitisation, excessive speculative activity in credit default swaps and the magnification of leverage and volatility. Comparable Islamic products are considered for the extent to which they facilitate the same precursors of market crises. Findings Innovation in secular financial markets has traditionally led to asset bubbles, underestimation of risks and market exuberance. Islamic banking constrains creativity by prohibiting risk transference and disconnection of financing activity from social context and economic purpose. As such, the latter reduces Schumpeterian creative destruction but at the cost of reduced investor choice and market liquidity. Restriction of the reallocation of risk between those who do not wish to hold it and those who do dampens innovation but would have prevented the trading of products which contributed to the credit crunch. Originality/value The constraining effect of Islamic banking upon creativity and innovation is considered alongside its capacity to reduce market volatility, speculation and systemic instability. Schumpeterian theory deepens the analysis in terms of the drivers of innovation and market collapse.

Speculative Fever: Investor Contagion in the Housing Bubble

Historical anecdotes abound of new investors being drawn into a booming asset market, only to suffer when the market turns. While the role of investor contagion in asset bubbles has been explored extensively in the theoretical literature, causal empirical evidence on the topic is much rarer. This paper studies the recent boom and bust in the US housing market and establishes that many novice investors entered the market as a direct result of observing investing activity of multiple forms in their own neighborhoods and that “infected” investors performed poorly relative to other investors along several dimensions. (JEL D84, G12, G51, R31)